Comparative Stock Performance Analysis of Leading Electric Vehicle Brands: Tesla, BYD, and NIO Using Python Programming Language

Abstract

This research paper aims to perform a comparative stock performance analysis of three leading electric vehicle brands: Tesla, BYD, and NIO, utilizing the Python programming language. The primary objective is to examine the financial trajectories of these companies by analyzing their historical stock prices, volatility, and return on investment over a defined period. Python programming language is also a key part of data analysis and data visualization. Methodologically, the study employs various Python libraries for data collection, preprocessing, and analysis, ensuring a robust and efficient analytical process. The key findings reveal distinct performance patterns and market behaviors for each company. Tesla demonstrated high volatility but significant long-term returns, while BYD showed consistent growth with moderate volatility. NIO, as a newer entrant, exhibited rapid growth with higher short-term risks. The conclusions drawn from this study provide valuable insights into the financial health and market positioning of these EV giants. By leveraging Python's powerful data analysis capabilities, this research not only enhances understanding of stock performance in the EV sector but also offers a practical framework for investors and analysts.